Abstract: A three-dimensional force loading device for a motor spindle is provided, and relates to the field of motor spindle testing. The device including a bottom plate; a torque loading assembly configured for testing torque performance of the motor spindle, and the torque loading assembly is in transmission connection with the motor spindle; a sleeve shell rotatably sleeved on the motor spindle, the sleeve shell is fixed along an axis direction of the motor spindle; a radial force loading assembly configured for testing radial force performance of the motor spindle, and the radial force loading assembly is fixedly connected with the sleeve shell; an axial force loading assembly configured for testing axial force performance of the motor spindle; and a intermediate force transmission mechanism connected with the sleeve shell and the axial force loading assembly.

Abstract: A three-dimensional force loading device for a motor spindle is provided, and relates to the field of motor spindle testing. The device including a bottom plate; a torque loading assembly configured for testing torque performance of the motor spindle, and the torque loading assembly is in transmission connection with the motor spindle; a sleeve shell rotatably sleeved on the motor spindle, the sleeve shell is fixed along an axis direction of the motor spindle; a radial force loading assembly configured for testing radial force performance of the motor spindle, and the radial force loading assembly is fixedly connected with the sleeve shell; an axial force loading assembly configured for testing axial force performance of the motor spindle; and a intermediate force transmission mechanism connected with the sleeve shell and the axial force loading assembly.

Abstract: The disclosure discloses a Fourier analysis method with a variable sampling frequency, including the following steps: S100 preliminarily sampling a to-be-analyzed signal by comparing an initially set sampling frequency, and further analyzing its fundamental frequency and fundamental amplitude value by Fourier analysis; S200 preliminarily judging the fundamental amplitude value obtained through analysis to determine a sampling frequency meeting integer period truncation, and resampling the signal; S300 performing Fourier analysis on the sampled signal, and determining an optimum sampling frequency, i.e., an optimum sampling frequency both meeting the integer period truncation and meeting no spectrum leakage, by a three-spectral line method; and S400 resampling the signal to obtain a frequency and amplitude value composition of each harmonic.

Abstract: Systems and methods involve filling missing attribute values from unstructured text. A computing device may provide a plurality of items, such as an item catalog for an electronic marketplace. When an item is found to have a missing attribute value, a plurality of existing values for that attribute is compiled by mining other items. Text associated with the item is parsed to determine possible values for the attribute. From those possible values, the most likely value is identified and the missing attribute value is populated with that value.

Abstract: A thrust compensation system of a dual-winding voice coil motor, which is used for driving the voice coil motor having main windings (100) and secondary windings (200), wherein the secondary windings (200) of the voice coil motor are between each pair of the main windings (100).

Abstract: A thrust compensation system of a dual-winding voice coil motor, which is used for driving the voice coil motor having main windings (100) and secondary windings (200), wherein the secondary windings (200) of the voice coil motor are between each pair of the main windings (100).

Abstract: Systems and methods involve filling missing attribute values from unstructured text. A computing device may provide a plurality of items, such as an item catalog for an electronic marketplace. When an item is found to have a missing attribute value, a plurality of existing values for that attribute is compiled by mining other items. Text associated with the item is parsed to determine possible values for the attribute. From those possible values, the most likely value is identified and the missing attribute value is populated with that value.